{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Manipulating kernels\n",
    "\n",
    "\n",
    "GPflow comes with a range of kernels that can be combined to make new kernels. In this notebook, we examine some of the kernels, show how kernels can be combined, discuss the active_dims feature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import gpflow\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('ggplot')\n",
    "import tensorflow as tf\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## First example\n",
    "\n",
    "Here is how to create a Matern 3/2 covariance kernel. The only required argument is the dimension of the input space over which the kernel is defined but we will also give provide values for the lengthscale and the variance (if we don't they both have `1.0` as default value)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "k = gpflow.kernels.Matern32(input_dim=1, variance=10., lengthscales=2.)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that the values we specified for the `variance` and `lengthscales` are **float**. We can get information about the kernel using `print(k)` (plain text) or, in a notebook, simply by entering the kernel name `k`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>class</th>\n",
       "      <th>prior</th>\n",
       "      <th>transform</th>\n",
       "      <th>trainable</th>\n",
       "      <th>shape</th>\n",
       "      <th>fixed_shape</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Matern32/lengthscales</th>\n",
       "      <td>Parameter</td>\n",
       "      <td>None</td>\n",
       "      <td>+ve</td>\n",
       "      <td>True</td>\n",
       "      <td>()</td>\n",
       "      <td>True</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Matern32/variance</th>\n",
       "      <td>Parameter</td>\n",
       "      <td>None</td>\n",
       "      <td>+ve</td>\n",
       "      <td>True</td>\n",
       "      <td>()</td>\n",
       "      <td>True</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "<gpflow.kernels.Matern32 at 0x7f7ff5f76128>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "k"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The parameter values can be accessed and assigned new values with the same syntax as for models:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.0\n",
      "0.5\n"
     ]
    }
   ],
   "source": [
    "print(k.lengthscales.value)\n",
    "k.lengthscales = .5\n",
    "print(k.lengthscales.value)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, we can compute the covavariance matrices using the methods `compute_K` or `compute_K_symm`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f7f9862ca58>]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X1 = np.array([[0.]])\n",
    "X2 = np.linspace(-2, 2, 101).reshape(-1, 1)\n",
    "\n",
    "K21 = k.compute_K(X2, X1)   # cov(f(X2), f(X1)), matrix with shape [101, 1]\n",
    "K22 = k.compute_K_symm(X2)  # matrix with shape [101, 101], same output as k.compute_K(X2, X2)\n",
    "\n",
    "# plotting\n",
    "plt.figure()\n",
    "plt.plot(X2, K21)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Implemented Kernels\n",
    "\n",
    "GPflow comes with lots of standard kernels. There are a couple of very simple kernels which produce constant functions, linear functions and white noise functions:\n",
    "\n",
    " * gpflow.kernels.Constant\n",
    "\n",
    " * gpflow.kernels.Linear\n",
    "\n",
    " * gpflow.kernels.White\n",
    "\n",
    "And some stationary functions which produce samples with varying degrees of smoothness:\n",
    "\n",
    " * gpflow.kernels.Exponential and gpflow.kernels.Matern12\n",
    "\n",
    " * gpflow.kernels.Matern32\n",
    "\n",
    " * gpflow.kernels.Matern52\n",
    "\n",
    " * gpflow.kernels.SquaredExponential (also known as gpflow.kernels.RBF)\n",
    "\n",
    " * gpflow.kernels.RationalQuadratic\n",
    "\n",
    "And two kernels which produce periodic samples:\n",
    "\n",
    " * gpflow.kernels.Cosine\n",
    "\n",
    " * gpflow.kernels.Periodic\n",
    " \n",
    "Other kernels that are implemented in core GPflow:\n",
    "    \n",
    " * gpflow.kernels.Polynomial\n",
    "\n",
    " * gpflow.kernels.ArcCosine (\"neural network kernel\")\n",
    "\n",
    " * gpflow.kernels.Coregion\n",
    " \n",
    "Let's define some plotting utils functions and have a look at samples from the prior for some of them:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 8 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plotkernelsample(k, ax, xmin=-3, xmax=3):\n",
    "    xx = np.linspace(xmin, xmax, 100)[:,None]\n",
    "    K = k.compute_K_symm(xx)\n",
    "    ax.plot(xx, np.random.multivariate_normal(np.zeros(100), K, 3).T)\n",
    "    ax.set_title(k.__class__.__name__)\n",
    "    \n",
    "np.random.seed(27)\n",
    "f, axes = plt.subplots(2, 4, figsize=(12, 6), sharex=True, sharey=True)\n",
    "plotkernelsample(gpflow.kernels.Matern12(1), axes[0,0])\n",
    "plotkernelsample(gpflow.kernels.Matern32(1), axes[0,1])\n",
    "plotkernelsample(gpflow.kernels.Matern52(1), axes[0,2])\n",
    "plotkernelsample(gpflow.kernels.RBF(1), axes[0,3])\n",
    "plotkernelsample(gpflow.kernels.Constant(1), axes[1,0])\n",
    "plotkernelsample(gpflow.kernels.Linear(1), axes[1,1])\n",
    "plotkernelsample(gpflow.kernels.Cosine(1), axes[1,2])\n",
    "plotkernelsample(gpflow.kernels.Periodic(1), axes[1,3])\n",
    "axes[0,0].set_ylim(-3, 3);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Combining kernels\n",
    "Valid kernels can be made by adding and multiplying kernels. To do this in GPflow, you can add or multiply intances of kernels, which creates a new kernel with the parameters of the old ones. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "k1 = gpflow.kernels.Matern12(input_dim=1)\n",
    "k2 = gpflow.kernels.Linear(input_dim=1)\n",
    "\n",
    "k3 = k1 + k2\n",
    "k4 = k1 * k2\n",
    "\n",
    "def plotkernelfunction(k, ax, xmin=-3, xmax=3, other=0):\n",
    "    xx = np.linspace(xmin, xmax, 200)[:,None]\n",
    "    ax.plot(xx, k.compute_K(xx, np.zeros((1,1)) + other))\n",
    "    ax.set_title(k.__class__.__name__ + ' k(x, %f)'%other)\n",
    "\n",
    "f, axes = plt.subplots(2, 2, figsize=(12, 6), sharex=True)\n",
    "plotkernelfunction(k3, axes[0, 0], other=1.)\n",
    "plotkernelfunction(k4, axes[0, 1], other=1.)\n",
    "plotkernelsample(k3, axes[1, 0])\n",
    "plotkernelsample(k4, axes[1, 1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Kernels on multiple dimensions\n",
    "The first, obligatory argument to every kernel is *input_dim*, which in the above has been 1. to make a kernel which works on more inputs (columns of X), simply specify a different input_dim. \n",
    "\n",
    "Stationary kernels all have ARD options, which allows the user to have one lengthscale parameter per input. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>class</th>\n",
       "      <th>prior</th>\n",
       "      <th>transform</th>\n",
       "      <th>trainable</th>\n",
       "      <th>shape</th>\n",
       "      <th>fixed_shape</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Matern52/lengthscales</th>\n",
       "      <td>Parameter</td>\n",
       "      <td>None</td>\n",
       "      <td>+ve</td>\n",
       "      <td>True</td>\n",
       "      <td>()</td>\n",
       "      <td>True</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Matern52/variance</th>\n",
       "      <td>Parameter</td>\n",
       "      <td>None</td>\n",
       "      <td>+ve</td>\n",
       "      <td>True</td>\n",
       "      <td>()</td>\n",
       "      <td>True</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "<gpflow.kernels.Matern52 at 0x7f7f881435f8>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "k = gpflow.kernels.Matern52(input_dim=5)\n",
    "k"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
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       "      <th>Matern52/lengthscales</th>\n",
       "      <td>Parameter</td>\n",
       "      <td>None</td>\n",
       "      <td>+ve</td>\n",
       "      <td>True</td>\n",
       "      <td>(5,)</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>Matern52/variance</th>\n",
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       "      <td>None</td>\n",
       "      <td>+ve</td>\n",
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       "      <td>()</td>\n",
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     "execution_count": 9,
     "metadata": {},
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    }
   ],
   "source": [
    "k = gpflow.kernels.Matern52(input_dim=5, ARD=True)\n",
    "k"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The lengthscales can also be initialised when the object is created:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
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       "  <tbody>\n",
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       "      <th>Matern52/lengthscales</th>\n",
       "      <td>Parameter</td>\n",
       "      <td>None</td>\n",
       "      <td>+ve</td>\n",
       "      <td>True</td>\n",
       "      <td>(5,)</td>\n",
       "      <td>True</td>\n",
       "      <td>[0.1, 0.2, 5.0, 5.0, 5.0]</td>\n",
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       "    <tr>\n",
       "      <th>Matern52/variance</th>\n",
       "      <td>Parameter</td>\n",
       "      <td>None</td>\n",
       "      <td>+ve</td>\n",
       "      <td>True</td>\n",
       "      <td>()</td>\n",
       "      <td>True</td>\n",
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      "text/plain": [
       "<gpflow.kernels.Matern52 at 0x7f7f88128748>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "k = gpflow.kernels.Matern52(input_dim=5, lengthscales=np.array([.1, .2, 5., 5., 5.]))\n",
    "k"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Active dimensions\n",
    "\n",
    "When combining kernels, it's often helpful to have bits of the kernel working on different dimensions. For example, to model a function that is linear in the first dimension and smooth in the second, we could use a combination of Linear and Matern52 kernels, one for each dimension.\n",
    "\n",
    "To tell GPflow which dimension a kernel applies to, one specifies the active_dims, which is a list of integers. Note that the `input_dim` of the kernel corresponds to the length of the `active_dims` vector.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Sum/kernels/0/variance</th>\n",
       "      <td>Parameter</td>\n",
       "      <td>None</td>\n",
       "      <td>+ve</td>\n",
       "      <td>True</td>\n",
       "      <td>()</td>\n",
       "      <td>True</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sum/kernels/1/lengthscales</th>\n",
       "      <td>Parameter</td>\n",
       "      <td>None</td>\n",
       "      <td>+ve</td>\n",
       "      <td>True</td>\n",
       "      <td>()</td>\n",
       "      <td>True</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sum/kernels/1/variance</th>\n",
       "      <td>Parameter</td>\n",
       "      <td>None</td>\n",
       "      <td>+ve</td>\n",
       "      <td>True</td>\n",
       "      <td>()</td>\n",
       "      <td>True</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
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       "<gpflow.kernels.Sum at 0x7f7f8804f6d8>"
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     },
     "execution_count": 11,
     "metadata": {},
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    }
   ],
   "source": [
    "k1 = gpflow.kernels.Linear(1, active_dims=[0])\n",
    "k2 = gpflow.kernels.Matern52(1, active_dims=[1])\n",
    "k = k1 + k2\n",
    "\n",
    "k"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## See also\n",
    "\n",
    "GPflow makes it easy to define new covariance functions. This is covered in the notebook [kernel design](../tailor/kernel_design.ipynb)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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